hybrid.utils.bqm_reduced_to#

bqm_reduced_to(bqm, variables, sample, keep_offset=True)[source]#

Reduce a binary quadratic model by fixing values of some variables.

The function is optimized for len(variables) ~ len(bqm), that is, for small numbers of fixed variables.

Parameters:

  • bqm (dimod.BinaryQuadraticModel) – Binary quadratic model (BQM).

  • variables (list/set) – Subset of variables to keep in the reduced BQM.

  • sample (dict/list) – Mapping of variable labels to values or a list when labels are sequential integers. Must include all variables not specified in variables.

  • keep_offset (bool, optional, default=True) – If false, set the reduced binary quadratic model’s offset to zero; otherwise, uses the caluclated energy offset.

Returns:

A reduced BQM.

Return type:

dimod.BinaryQuadraticModel

Examples

This example reduces a 3-variable BQM to two variables.

>>> import dimod
>>> bqm = dimod.BQM({}, {'ab': -1, 'bc': -1, 'ca': -1}, 0, 'BINARY')
>>> sample = {'a': 1, 'b': 1, 'c': 0}
>>> subbqm = bqm_reduced_to(bqm, ['a', 'b'], sample)
>>> len(subbqm)
2